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Most universities have responded to AI by rewriting assessment policies and running prompt-writing workshops. Context engineering demands something different: infrastructure decisions that commit institutions to a direction. This post explains what context engineering involves, why it matters for health professions education, and why the gap between changing words and changing structures is where most institutions are stuck.
Higher education institutions face persistent pressure to demonstrate AI engagement, often resulting in 'innovation theatre' — the performance of transformation without corresponding structural change. This essay presents a diagnostic framework distinguishing between performative and structural AI integration across four domains: governance and accountability, resource architecture, learning systems, and boundary setting. Unlike linear maturity models, it reveals gaps between institutional rhetoric and operational reality. Three legitimate strategic positions — incremental, selective, and transformative — help institutions move from accidental drift toward conscious choice. Treating AI integration as ongoing strategic practice rather than fixed deployment ensures institutions preserve agency over technology decisions aligned with institutional values.